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All digests tagged Microservices
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The future of AI agents lies in specialization. We must move from 'god models' to thousands of hyper-scoped, domain-specific agents, requiring standardized runtimes and a microservices mindset.
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Running AI agents in production requires separating the 'brain' (LLM planning) from the 'hands' (deterministic harness). This approach treats agent harnesses as late-bound sagas, ensuring reliability and durability for complex, long-running workflows.
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Antigravity 2.0 introduces agent teams, powered by dynamic subagents, sidecars, and generative UI. This architecture allows complex tasks, like building an OS kernel, to be automated by swarms of specialized agents.
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Learn how AI is accelerating the modernization of mission-critical legacy systems, translating old code (Cobol, Mainframe) into modern, scalable architectures.
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Learn how to apply AI-Native Engineering practices to brownfield codebases, moving from maintenance mode to evolution. Discover the Strangler Fig Pattern and Branch by Extraction.
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